Just-in-Time Encoding Into Visual Working Memory Is Contingent Upon Constant Availability of External Information

Humans maintain an intricate balance between storing information in visual working memory (VWM) and just-in-time sampling of the external world, rooted in a trade-off between the cost of maintaining items in VWM versus retrieving information as it is needed. Previous studies have consistently shown that one prerequisite of just-in-time sampling is a high degree of availability of external information, and that introducing a delay before being able to access information led participants to rely less on the external world and more on VWM. However, these studies manipulated availability in such a manner that the cost of sampling was stable and predictable. It is yet unclear whether participants become less reliant on external information when it is more difficult to factor in the cost of sampling that information. In two experiments, participants copied an example layout from the left to the right side of the screen. In Experiment 1, intermittent occlusion of the example layout led participants to attempt to encode more items per inspection than when the layout was constantly available, but this did not consistently result in more correct placements. However, these findings could potentially be explained by inherent differences in how long the example layout could be viewed. Therefore in Experiment 2, the example layout only became available after a gaze-contingent delay, which could be constant or variable. Here, the introduction of any delay led to increased VWM load compared to no delay, although the degree of variability in the delay did not alter behaviour. These results reaffirm that the nature of when we engage VWM is dynamical, and suggest that any disruption to the continuous availability of external information is the main driver of increased VWM usage relative to whether availability is predictable or not.


Outcome variable Description
A Example grid inspections Calculated by counting how many times within a trial the participant made a saccade across the centre of the screen from the right side to the left side.In effect, this variable represents how often participants sampled externally by looking toward the example grid after focusing on the working-and resource area.We did not count crossings in which only the hourglass was fixated, and assumed that short fixations would be unlikely to allow for meaningful encoding (e.g., Bays et al., 2011).Therefore an inspection would only be counted if the example grid was viewed for at least 120ms before the participant crossed back towards the workingand resource area.

B
Fixations per inspection Computed by dividing the number of fixations within the boundaries of the example grid by the number of useful inspections.This variable approximates how much information participants attempted to take in each time they placed their overt attention on the example grid.

Items placed per inspection
Computed by dividing the number of correctly placed items per trial by the number of useful inspections made in that trial.It is an estimate of how many items participants (accurately) encoded during each inspection.

D Completion time (s)
Calculated from the start of the trial until all items were placed correctly, or until the 42-second timer was reached.Because the periods during which the example grid was occluded were not useless to participants (i.e., they could still place items during that time), only the time spent gazing at the hourglass in the location of the occluded example grid was subtracted from the completion time.

Errors per trial
An error constituted the attempted placement of any item in an incorrect slot in the working grid.A greater number of errors may reflect that items were encoded less accurately (Koevoet et al., 2023;van den Berg et al., 2012) or that participants had more liberal thresholds for the quality of memory representations that they were willing to act on (Sahakian et al., 2023).
F Exp1 Proportion spent waiting Expressed as the duration that participants spent gazing at the hourglass, divided by the actual duration with which the example grid was occluded during that trial.This measure effectively reflects the proportion of a trial that participants spent unproductively waiting.For example: In a trial in the Low condition, if the example grid was occluded for 12 seconds in total and a participant spent 600 ms gazing at the hourglass, the proportion spent waiting is 0.05.In the High condition, if the grid was occluded for 6 seconds in total and a participant spent 300 ms gazing at the hourglass, the proportion spent waiting is also 0.05.As such, the proportion that participants spent waiting was standardized between 0 and 1 and could be compared between conditions.
F Exp2 Time spent waiting (s) Represents how long participants gazed at the hourglass while the example grid was occluded, and provides an indication whether overall delay durations were similar between conditions in which a delay was present.

Figure 1 :
Figure 1: Distribution of generated delay durations in Experiment 2.

Table 1 :
Outcome measures used for analysis of both experiments.

Table 2 :
Outcomes of Bayesian Repeated-Measures ANOVAs, between the three delay conditions in Experiment 2 (constant, low variance, high variance).

Table 3 :
Statistical outcomes for Bayesian paired samples t-tests between the three delay conditions in Experiment 2, corrected for three comparisons.